
Webinar "Towards Transparent, Safe and Trustworthy AI for critical infrastructures"
This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.

Webinar: Knowledge-Assisted AI Applications for Real-World Network Infrastructure
This webinar showcases how the AI4REALNET project is driving innovation in critical infrastructure through advanced AI applications.

Uncertainty-Based Learning of a Lightweight Model for Multimodal Emotion Recognition
In this paper, the authors propose a lightweight neural network architecture that extracts and performs the analysis of multimodal information using the same audio and visual networks across multiple temporal segments.

CO2A – Contrastive Conditional domain Alignment
A novel unsupervised domain adaptation approach for action recognition from videos, inspired by recent literature on contrastive learning.

pygrank
pygrank is an open source framework to define, run and evaluate node ranking algorithms.

InDistill
InDistill enchances the effectiveness of the Knowledge Distillation procedure by leveraging the properties of channel pruning to both reduce the capacity gap between the models and retain the information geometry.